Can We Improve Physical Health Monitoring for Patients Taking Antipsychotics on a Mental Health Inpatient Unit?

Metabolic Monitoring for Adults Living with a Serious Mental Illness on a Second-Generation Antipsychotic Agent: A Scoping Review

Premature mortality in people living with a severe mental illness (SMI) is often attributed to multiple factors including the use of medicines such as antipsychotics. Second-generation antipsychotics (SGAs) are known to cause metabolic syndrome which can increase the risk of cardiovascular disease. Practice guidelines have recommended regular physical health monitoring, particularly of metabolic parameters, however, metabolic monitoring for people living with SMI using antipsychotics remains suboptimal. Therefore, highlighting the need for ongoing research. This scoping review aimed to provide an overview of current metabolic monitoring practices. We anticipate that this information will assist clinicians and policymakers and inform future research. The following databases were searched: MEDLINE (Ovid), Embase (Ovid), CINAHL (EBSCO), the Cochrane Database of Systemic Reviews (Wiley), APA PsycInfo (Ovid) and Scopus (Elsevier Science Publishers). The target group was adults (aged ≥ 18) diagnosed with SMI (including bipolar disorder, major depressive disorder and psychotic disorders) and taking SGAs. In total, 44 studies from 14 countries were retrieved. Our findings highlighted that most studies conducted in hospitals did not report on metabolic monitoring practices. Additionally, the roles and responsibilities of healthcare professionals in metabolic monitoring for SMI were infrequently described and parameters such as waist circumference and BMI were often poorly monitored. The scoping review highlights that no streamlined approach towards metabolic monitoring currently exists. There is a need to stipulate and define the roles and responsibilities of all health professionals involved in metabolic monitoring in SMI to optimise care for these individuals. Moreover, there is a need for ongoing research, particularly in the community setting, to promote increased accessibility to metabolic monitoring for SMI.

Impact of institutional quality improvement initiatives on metabolic monitoring in mental disorder in patients treated with antipsychotics: A meta-analysis of intervention studies

Background

Compliance with guidelines regarding monitoring of metabolic adverse effects induced by antipsychotics has been consistently low. We characterised and evaluated the quality of institutional quality improvement (QI) interventions designed to address disparities between guidelines and real-world practices. Furthermore, we assessed the impact of these interventions on the screening and management of metabolic risks for inpatients receiving treatment with antipsychotic medications.

Methods

We conducted a meta-analysis of institutional QI intervention studies aimed at improving antipsychotic-associated metabolic risk monitoring in hospitalised mental disease patients. Relevant studies were identified through searches conducted in the Embase and PubMed databases, as well as by reviewing previous reviews and meta-analyses. Quantitative analyses were performed, calculating odds ratios (ORs) and 95% confidence intervals (CIs) to assess the impact of QI programmes on guideline adherence in clinical practice.

Results

We identified 12 intervention studies (n = 10 128 and n = 2667 patients in the pre-and post-intervention groups, respectively) and included them in our meta-analysis. QI interventions demonstrated effectiveness in bridging the guideline-practice gap in monitoring antipsychotic-induced metabolic adverse effects, as supported by the ORs and 95% CIs for post-intervention monitoring of plasma glucose, lipids, and blood pressure (BP) vs the pre-intervention period being OR = 6.90 (95% CI = 1.51-31.48), OR = 5.39 (95% CI = 4.01-7.24), and OR = 4.81 (95% CI = 1.23-18.79), respectively. Only 33.3% (4/12) of studies reported screening rates for all four metabolic parameters (plasma glucose, lipids, weight/body mass index (BMI), and BP). The median rates for metabolic screening of plasma glucose, lipids, and BP increased from 51.0-80.0%, 28.7-66.7%, and 91.7-95.8%, respectively. Up to 66.7% (8/12) of intervention studies lacked follow-up measures to treat or manage identified risks in hospitalised psychiatric patients, such as patient referrals, prescription of medications, and switching of antipsychotics. The odds of monitoring weight/BMI and glucose were greatest when QI programmes involved the participation of multidisciplinary health care professionals and patients, yielding OR = 3.35 (95% CI = 2.45-4.59) and OR = 57.51 (95% CI = 24.11-137.21), respectively.

Conclusions

Institutional QI interventions were effective in enhancing monitoring practices in alignment with established guidelines for metabolic risk screening among hospitalised patients with mental disorders maintained on antipsychotic medications. Future institutional QI programmes should incorporate multidisciplinary strategies involving patient engagement and extend their focus beyond screening to incorporate follow-up risk management strategies once risks have been identified.

Registration

PROSPERO CRD42023452138.

[Antipsychotic prescription prevalence and metabolic monitoring of patients under chronic treatment]

Introduction

Antipsychotics agents increase morbidity and mortality due to their metabolic impact. Information on its prescription and follow-up is scarce. The objective of this study was to estimate the chronic antipsychotic prescription prevalence and to evaluate the metabolic monitoring of patients treated with these medications.

Methods

We examined a retrospective cohort of patients older than 18 years treated in the outpatient setting of a hospital in Argentina. The crude and adjusted prevalence of chronic antipsychotic prescription was estimated by indirect standardization of the World Health Organization population, with its confidence interval (95%). It was evaluated whether the patients had biochemical determinations, systolic blood pressure (SBP), and body mass index (BMI) at the beginning and at 12 months of their treatment.

Results

The crude antipsychotic prescription prevalence was 23.8 ‰ (95% CI 23.0 - 24.6) and the adjusted prevalence was 10.1 ‰ (95% CI 9.5-10.7). 3702 patients were evaluated. The male:female ratio was 0.6. Median age 77.5 years (IQR 25-75: 59.5-86.1). Quetiapine was the most frequently prescribed. Initial determinations: Lipid profile 1804 (48.7%), blood glucose 2034 (54.9%), SBP 2546 (68.8%) and BMI 1584 (42.8%). At 12 months: Lipid profile 680 (18.4%), blood glucose 898 (24.3%), SAT 1609 (43.5%), and BMI 1584 (21.7%).

Conclusions

We observed a higher prevalence of atypical antipsychotic prescription in the elderly and female population and scarce registry of biochemical determinations for adverse effects follow-up.

[Antipsychotic prescription prevalence and metabolic monitoring of patients under chronic treatment]

INTRODUCTION

Antipsychotics agents increase morbidity and mortality due to their metabolic impact. Information on its prescription and follow-up is scarce. The objective of this study was to estimate the chronic antipsychotic prescription prevalence and to evaluate the metabolic monitoring of patients treated with these medications.

METHODS

We examined a retrospective cohort of patients older than 18 years treated in the outpatient setting of a hospital in Argentina. The crude and adjusted prevalence of chronic antipsychotic prescription was estimated by indirect standardization of the World Health Organization population, with its confidence interval (95%). It was evaluated whether the patients had biochemical determinations, systolic blood pressure (SBP), and body mass index (BMI) at the beginning and at 12 months of their treatment.

RESULTS

The crude antipsychotic prescription prevalence was 23.8 ‰ (95% CI 23.0 - 24.6) and the adjusted prevalence was 10.1 ‰ (95% CI 9.5-10.7). 3702 patients were evaluated. The male:female ratio was 0.6. Median age 77.5 years (IQR 25-75: 59.5-86.1). Quetiapine was the most frequently prescribed. Initial determinations: Lipid profile 1804 (48.7%), blood glucose 2034 (54.9%), SBP 2546 (68.8%) and BMI 1584 (42.8%). At 12 months: Lipid profile 680 (18.4%), blood glucose 898 (24.3%), SAT 1609 (43.5%), and BMI 1584 (21.7%).

CONCLUSIONS

We observed a higher prevalence of atypical antipsychotic prescription in the elderly and female population and scarce registry of biochemical determinations for adverse effects follow-up.

Improvement of Inpatient Psychiatric Facility Quality Reporting program measure: Screening for metabolic disorders through pharmacy collaborative practice agreement

BACKGROUND

Second-generation antipsychotics are associated with lower risks of extrapyramidal symptoms, including tardive dyskinesia. However, many second-generation antipsychotics are associated with metabolic adverse effects, including weight gain, impaired blood glucose control, and hyperlipidemia. Metabolic monitoring for patients prescribed antipsychotic medication is 1 of several measures of the Centers for Medicare & Medicaid Services' Inpatient Psychiatric Facility Quality Reporting program. Screening for metabolic disorders (SMD) must be obtained within the previous 365 days before the hospital discharge date. National data suggest that compliance with this measure is low.

OBJECTIVE

To improve compliance of metabolic monitoring by 20% while ensuring that the quality improvement interventions did not cause any unintended adverse effects on other aspects of our system.

PRACTICE DESCRIPTION

This quality initiative was conducted at a large, 2000-bed academic medical center with approximately 80 inpatient psychiatric beds.

PRACTICE INNOVATION

To improve the metabolic screening rates, a pharmacist collaborative practice agreement (CPA) was established as part of a quality improvement project. Previously, there were no formal processes at the institution to ensure that appropriate laboratory tests were conducted.

EVALUATION METHODS

Using an uncontrolled before-and-after design, SMD data were gathered from 6 months before and 6 months after CPA implementation. Pearson chi-square test or Fisher exact test were used to compare the pre- and postintervention groups in this quasi-experimental design.

RESULTS

Compared with the preintervention period, compliance of SMD monitoring increased by 21.2% in the postintervention phase-from 69.2% to 90.4% (P < 0.001).

CONCLUSION

The empowerment of clinical pharmacists with a CPA significantly improved guideline-concordant metabolic monitoring of antipsychotics. These findings may have significant impact on the approach to the safe use of these essential psychotropic medications and provide a framework for other inpatient mental health facilities to optimally use the skills of their interdisciplinary team.

Risk Factors of Metabolic Syndrome Among Patients Receiving Antipsychotics: A Retrospective Study

This study aimed to assess the differential effects of first-generation (FGA) and second-generation antipsychotics (SGA) on the prevalence of risk factors for metabolic syndrome among mentally ill patients in Qatar. We also wanted to check if there is proper adherence with the guidelines for prescribing antipsychotics and the monitoring of metabolic effects in this population. We collected the available retrospective data (socio-demographic, psychiatric, anthropometric, and metabolic measures) from the records of 439 patients maintained on antipsychotics. The majority were males, married, employed, having a psychotic disorder, and receiving SGA. Patients on SGA showed more obesity, higher BP, and more elevated triglycerides compared to those on FGA. The prevalence of the abnormal metabolic measures was high in this sample, but those on SGA showed a significantly higher prevalence of abnormal body mass index and BP. Obesity and hypertension were common in patients maintained on antipsychotics, especially those on SGA. Polypharmacy was common, and many metabolic measures were not monitored properly in those maintained on antipsychotics. More prospective studies with guided monitoring of the patients' clinical status and metabolic changes are needed to serve better this population of patients.